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Space–Time Patterns of Urban Sprawl, a 1D Cellular Automata and Microeconomic Approach

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  • Geoffrey Caruso

    (Geography and Spatial Planning Research Centre, IPSE, University of Luxembourg, Route de Diekirch, BP2, L-7220 Walferdange, Luxembourg)

  • Dominique Peeters

    (Centre for Operations Research and Econometrics, Universite Catholique de Louvain, Louvain-la-Neuve, Belgium)

  • Jean Cavailhes

    (UMR CESAER, Institut National de Recherche Agronomique, 21065 Dijon, France)

  • Mark Rounsevell

    (School of Geosciences, University of Edinburgh, Edinburgh EH9 3JW, Scotland)

Abstract

We present a theoretical model of residential growth that emphasises the path-dependent nature of urban sprawl patterns. The model is founded on the monocentric urban economic model and uses a cellular automata (CA) approach to introduce endogenous neighbourhood effects. Households are assumed both to like and to dislike the density of their neighbourhood, and are assumed to trade-off this density with housing space consumption and commuting costs. Discontinuous spatial patterns emerge from that trade-off, with the size of suburban clusters varying with time and distance to the centre. We use space–time diagrams inspired from 1D elementary CA to visualise changes in spatial patterns through time and space, and undertake sensitivity analyses to show how the pattern and timing of sprawl are affected by neighbourhood preferences, income level, commuting costs, or by imposing a green belt.

Suggested Citation

  • Geoffrey Caruso & Dominique Peeters & Jean Cavailhes & Mark Rounsevell, 2009. "Space–Time Patterns of Urban Sprawl, a 1D Cellular Automata and Microeconomic Approach," Environment and Planning B, , vol. 36(6), pages 968-988, December.
  • Handle: RePEc:sae:envirb:v:36:y:2009:i:6:p:968-988
    DOI: 10.1068/b34009
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    References listed on IDEAS

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    1. Fujita,Masahisa, 1991. "Urban Economic Theory," Cambridge Books, Cambridge University Press, number 9780521396455, September.
    2. Caruso, Geoffrey & Peeters, Dominique & Cavailhes, Jean & Rounsevell, Mark, 2007. "Spatial configurations in a periurban city. A cellular automata-based microeconomic model," Regional Science and Urban Economics, Elsevier, vol. 37(5), pages 542-567, September.
    3. Shih-Kung Lai, 2003. "On transition rules of complex structures in one-dimensional cellular automata: Some implicaltions for urban change," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 37(2), pages 337-352, May.
    4. Bucholtz, Shawn & Geoghegan, Jacqueline & Lynch, Lori, 2003. "Capitalization of Open Spaces into Housing Values and the Residential Property Tax Revenue Impacts of Agricultural Easement Programs," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 32(1), pages 1-13, April.
    5. Anderson, Soren T. & West, Sarah E., 2006. "Open space, residential property values, and spatial context," Regional Science and Urban Economics, Elsevier, vol. 36(6), pages 773-789, November.
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    Cited by:

    1. Akamatsu, Takashi & Fujishima, Shota & Takayama, Yuki, 2017. "Discrete-space agglomeration model with social interactions: Multiplicity, stability, and continuous limit of equilibria," Journal of Mathematical Economics, Elsevier, vol. 69(C), pages 22-37.
    2. Akamatsu, Takashi & Fujishima, Shota & Takayama, Yuki, 2014. "On Stable Equilibria in Discrete-Space Social Interaction Models," MPRA Paper 55938, University Library of Munich, Germany.
    3. Verstegen, Judith A. & Goch, Katarzyna, 2022. "Pattern-oriented calibration and validation of urban growth models: Case studies of Dublin, Milan and Warsaw," Land Use Policy, Elsevier, vol. 112(C).

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